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Automatic Image-Driven Segmentation of Left  Ventricle in Cardiac Cine MRI
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This study investigates a fully automatic left ventricle segmentation method from cine short axis MR images. Advantages of this method include that it: 1) is image-driven and does not require manually drawn initial contours. 2) provides not only endocardial [...]

Segmentation of the Left Ventricle from Cine MR Images Using a Comprehensive Approach
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Segmentation of the left ventricle is important in assessment of cardiac functional parameters. Currently, manual segmentation is the gold standard for acquiring these parameters and can be time-consuming. Therefore, accuracy and automation are two important [...]

LV Challenge LKEB Contribution: Fully Automated Myocardial Contour Detection
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In this paper a contour detection method is described and evaluated on the evaluation data sets of the Cardiac MR Left Ventricle Segmentation Challenge as part of MICCAI 2009’s 3D Segmentation Challenge for Clinical Applications. The proposed method, using [...]

Segmenting the Left Ventricle in 3D Using a Coupled ASM and a Learned Non-Rigid Spatial Model
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This paper presents a new approach to higher dimensional segmentation. We present an extended Active Shape Model (ASM) formulation for the segmentation of multi-contour anatomical structures. We employ coupling and weighting schemes to improve the robustness [...]

An open, clinically-validated database of 3D+t cine-MR images of the left ventricle with associated manual and automated segmentation
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In this paper, we describe a database of cine-MR (3D+t) images of the left ventricle. This database contains the voxel data, one automated and two manual segmentations for each sequence of images. The segmentations are validated from a clinical point of [...]


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